001     599818
005     20250724132549.0
024 7 _ |a 10.1109/ISMAR59233.2023.00039
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037 _ _ |a PUBDB-2023-07544
041 _ _ |a English
100 1 _ |a Rolff, Tim
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111 2 _ |a 2023 IEEE International Symposium on Mixed and Augmented Reality
|g ISMAR
|c Sydney
|d 2023-10-16 - 2023-10-20
|w Australia
245 _ _ |a VRS-NeRF: Accelerating Neural Radiance Field Rendering with Variable Rate Shading
260 _ _ |c 2023
|b IEEE
295 1 0 |a 2023 IEEE International Symposium on Mixed and Augmented Reality (ISMAR) : [Proceedings] - IEEE, 2023. - ISBN 979-8-3503-2838-7 - doi:10.1109/ISMAR59233.2023.00039
300 _ _ |a 243 - 252
336 7 _ |a CONFERENCE_PAPER
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520 _ _ |a Recent advancements in Neural Radiance Fields (NeRF) provide enormous potential for a wide range of Mixed Reality (MR) applications. However, the applicability of NeRF to real-time MR systems is still largely limited by the rendering performance of NeRF. In this paper, we present a novel approach for Variable Rate Shading for Neural Radiance Fields (VRS-NeRF). In contrast to previous techniques, our approach does not require training multiple neural networks or re-training of already existing ones, but instead utilizes the raytracing properties of NeRF. This is achieved by merging rays depending on a variable shading rate, which reduces the overall number of queries to the neural network. We demonstrate the generalizability of our approach by implementing three alternative functions for the determination of the shading rate. The first method uses the gaze of users to effectively implement a foveated rendering technique in NeRF. For the other two techniques, we utilize shading rates based on edges and saliency. Based on a psychophysical experiment and multiple image-based metrics, we suggest a set of parameters for each technique, yielding an optimal tradeoff between rendering performance gain and perceived visual quality.
536 _ _ |a 621 - Accelerator Research and Development (POF4-621)
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536 _ _ |a HIDSS-0002 - DASHH: Data Science in Hamburg - Helmholtz Graduate School for the Structure of Matter (2019_IVF-HIDSS-0002)
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588 _ _ |a Dataset connected to CrossRef Conference
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700 1 _ |a Schmidt, Susanne
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700 1 _ |a Li, Ke
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700 1 _ |a Steinicke, Frank
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700 1 _ |a Frintrop, Simone
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773 _ _ |a 10.1109/ISMAR59233.2023.00039
856 4 _ |u https://bib-pubdb1.desy.de/record/599818/files/VRS-NeRF_Accelerating_Neural_Radiance_Field_Rendering_with_Variable_Rate_Shading.pdf
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856 4 _ |u https://bib-pubdb1.desy.de/record/599818/files/VRS-NeRF_Accelerating_Neural_Radiance_Field_Rendering_with_Variable_Rate_Shading.pdf?subformat=pdfa
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910 1 _ |a Deutsches Elektronen-Synchrotron
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913 1 _ |a DE-HGF
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914 1 _ |y 2023
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